Previous research has shown that drivers who get just one to two hours less than the recommended daily allowance in a 24-hour period nearly double their risk for a car crash.

For the study, led by Derk-Jan Dijk from the University of Surrey in the UK, 36 participants skipped one night of sleep.

During this 40-hour period of sleep deprivation, blood samples were taken and changes in the expression levels of thousands of genes were measured.

A machine learning algorithm identified a subset of 68 genes and with 92 per cent accuracy could detect whether a sample was from a sleep-deprived or well-rested individual.

This discovery paves the way for a future test which will be able to assess if a driver was sleep deprived, researchers said.

“We all know that insufficient sleep poses a significant risk to our physical and mental health, particularly over a period of time,” said Emma Laing, a senior lecturer at the University of Surrey.

“However, it is difficult to independently assess how much sleep a person has had, making it difficult for the police to know if drivers were fit to drive, or for employers to know if staff are fit for work,” said Laing.

“Identifying these biomarkers is the first step to developing a test which can accurately calculate how much sleep an individual has had,” said Simon Archer, a professor at the University of Surrey.

“The very existence of such biomarkers in the blood after only a period of 24-hour wakefulness shows the physiological impact a lack of sleep can have on our body,” he said.

“This is a test for acute total sleep loss; the next step is to identify biomarkers for chronic insufficient sleep, which we know to be associated with adverse health outcomes,” said Dijk.